Regional Cerebral Blood Flow Changes in Healthy Ageing and Alzheimer's Disease: A Narrative Review.

BACKGROUND: Cerebral blood flow is known to decline with increasing age and is a potential biomarker to distinguish between healthy and unhealthy ageing, where healthy ageing is defined as an absence of comorbidities in senescence. This review aims to synthesize evidence of cerebral blood flow changes over multiple brain regions, for use as a clinical reference or for in silico modelling. SUMMARY: The search identified 1,087 studies, of which 33 met the inclusion criteria to map the difference in cerebral blood flow reduction between healthy ageing and Alzheimer's disease. Analysis was also performed on the effect of imaging modality and brain region functionality as potential confounding factors. KEY MESSAGES: No significant difference was found between the specific functionality of a brain region and cerebral blood flow in healthy ageing (p = 0.65) or Alzheimer's disease (p = 0.42). Arterial spin labelling MRI imaging was shown to measure statistically larger decreases in flow in both healthy ageing (p = 0.0001) and Alzheimer's disease (p = 0.0465). Cerebral blood flow was shown to decrease 0.3-0.5% per year in healthy ageing, which increased to a decline of 2-5% per year in Alzheimer's disease. There was large variability both between and within individual brain regions, and this variability increased greatly in Alzheimer's disease. Future studies would add value by taking more cerebral blood flow measurements during Alzheimer's disease progression and by investigating ageing with comorbidities such as hypertension.

Modelling the impact of clot fragmentation on the microcirculation after thrombectomy.

Many ischaemic stroke patients who have a mechanical removal of their clot (thrombectomy) do not get reperfusion of tissue despite the thrombus being removed. One hypothesis for this 'no-reperfusion' phenomenon is micro-emboli fragmenting off the large clot during thrombectomy and occluding smaller blood vessels downstream of the clot location. This is impossible to observe in-vivo and so we here develop an in-silico model based on in-vitro experiments to model the effect of micro-emboli on brain tissue. Through in-vitro experiments we obtain, under a variety of clot consistencies and thrombectomy techniques, micro-emboli distributions post-thrombectomy. Blood flow through the microcirculation is modelled for statistically accurate voxels of brain microvasculature including penetrating arterioles and capillary beds. A novel micro-emboli algorithm, informed by the experimental data, is used to simulate the impact of micro-emboli successively entering the penetrating arterioles and the capillary bed. Scaled-up blood flow parameters-permeability and coupling coefficients-are calculated under various conditions. We find that capillary beds are more susceptible to occlusions than the penetrating arterioles with a 4x greater drop in permeability per volume of vessel occluded. Individual microvascular geometries determine robustness to micro-emboli. Hard clot fragmentation leads to larger micro-emboli and larger drops in blood flow for a given number of micro-emboli. Thrombectomy technique has a large impact on clot fragmentation and hence occlusions in the microvasculature. As such, in-silico modelling of mechanical thrombectomy predicts that clot specific factors, interventional technique, and microvascular geometry strongly influence reperfusion of the brain. Micro-emboli are likely contributory to the phenomenon of no-reperfusion following successful removal of a major clot.

Clinical correlations and long-term follow-up in 100 patients with sarcoglycanopathies.

BACKGROUND AND PURPOSE: To describe a large series of patients with α, ß, and γ sarcoglycanopathies (LGMD-R3, R4, and R5) and study phenotypic correlations and disease progression. METHODS: A multicentric retrospective study in four centers in the Paris area collecting neuromuscular, respiratory, cardiac, histologic, and genetic data. The primary outcome of progression was age of loss of ambulation (LoA); disease severity was established according to LoA before or after 18 years of age. Time-to-event analysis was performed. RESULTS: One hundred patients (54 γ-SG; 41 α-SG; 5 ß-SG) from 80 families were included. The γ-SG patients had earlier disease onset than α-SG patients (5.5 vs. 8 years; p = 0.022) and ß-SG patients (24.4 years). Axial muscle weakness and joint contractures were frequent and exercise intolerance was observed. At mean follow-up of 22.9 years, 65.3% of patients were wheelchair-bound (66.7% α-SG, 67.3% γ-SG, 40% ß-SG). Dilated cardiomyopathy occurred in all sarcoglycanopathy subtypes, especially in γ-SG patients (p = 0.01). Thirty patients were ventilated and six died. Absent sarcoglycan protein expression on muscle biopsy and younger age at onset were associated with earlier time to LoA (p = 0.021 and p = 0.002). Age at onset was an independent predictor of both severity and time to LoA (p = 0.0004 and p = 0.009). The α-SG patients showed genetic heterogeneity, whereas >90% of γ-SG patients carried the homozygous c.525delT frameshift variant. Five new mutations were identified. CONCLUSIONS: This large multicentric series delineates the clinical spectrum of patients with sarcoglycanopathies. Age at disease onset is an independent predictor of severity of disease and LoA, and should be taken into account in future clinical trials.

Guidance for the care of neuromuscular patients during the COVID-19 pandemic outbreak from the French Rare Health Care for Neuromuscular Diseases Network.

In France, the epidemic phase of COVID-19 caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) began in February 2020 and resulted in the implementation of emergency measures and a degradation in the organization of neuromuscular reference centers. In this special context, the French Rare Health Care for Neuromuscular Diseases Network (FILNEMUS) has established guidance in an attempt to homogenize the management of neuromuscular (NM) patients within the French territory. Hospitalization should be reserved for emergencies, the conduct of treatments that cannot be postponed, check-ups for which the diagnostic delay may result in a loss of survival chance, and cardiorespiratory assessments for which the delay could be detrimental to the patient. A national strategy was adopted during a period of 1 to 2months concerning treatments usually administered in hospitalization. NM patients treated with steroid/immunosuppressants for a dysimmune pathology should continue all of their treatments in the absence of any manifestations suggestive of COVID-19. A frequently asked questions (FAQ) sheet has been compiled and updated on the FILNEMUS website. Various support systems for self-rehabilitation and guided exercises have been also provided on the website. In the context of NM diseases, particular attention must be paid to two experimental COVID-19 treatments, hydroxycholoroquine and azithromycin: risk of exacerbation of myasthenia gravis and QT prolongation in patients with pre-existing cardiac involvement. The unfavorable emergency context related to COVID-19 may specially affect the potential for intensive care admission (ICU) for people with NMD. In order to preserve the fairest medical decision, a multidisciplinary working group has listed the neuromuscular diseases with a good prognosis, usually eligible for resuscitation admission in ICU and, for other NM conditions, the positive criteria suggesting a good prognosis. Adaptation of the use of noninvasive ventilation (NIV) make it possible to limit nebulization and continue using NIV in ventilator-dependent patients.

Investigating the effects of a penetrating vessel occlusion with a multi-scale microvasculature model of the human cerebral cortex.

The effect of the microvasculature on observed clinical parameters, such as cerebral blood flow, is poorly understood. This is partly due to the gap between the vessels that can be individually imaged in humans and the microvasculature, meaning that mathematical models are required to understand the role of the microvasculature. As a result, a multi-scale model based on morphological data was developed here that is able to model large regions of the human microvasculature. From this model, a clear layering of flow (and 1-dimensional depth profiles) was observed within a voxel, with the flow in the microvasculature being driven predominantly by the geometry of the penetrating vessels. It also appears that the pressure and flow are decoupled, both in healthy vasculatures and in those where occlusions have occurred, again due to the topology of the penetrating vessels shunting flow between them. Occlusion of a penetrating arteriole resulted in a very high degree of overlap of blood pressure drop with experimentally observed cell death. However, drops in blood flow were far more widespread, providing additional support for the theory that pericyte controlled regulation on the capillary scale likely plays a large part in the perfusion of tissue post-occlusion.

Prediction of long-term prognosis by heteroplasmy levels of the m.3243A>G mutation in patients with the mitochondrial encephalomyopathy, lactic acidosis and stroke-like episodes syndrome.

BACKGROUND AND PURPOSE: Our aim was to determine the prognostic value of urine and blood heteroplasmy in patients with the m.3243A>G mutation. METHODS: Adults with the m.3243A>G mutation referred to our institution between January 2000 and May 2014 were retrospectively included. The relationship between their baseline clinical characteristics, their mutation load in urine and blood, and major adverse events (MAEs) during follow-up, defined as medical complications requiring a hospitalization or complicated by death, was studied. RESULTS: Of the 43 patients (age 45.6 ± 13.3 years) included in the study, 36 patients were symptomatic, including nine with evidence of focal brain involvement, and seven were asymptomatic. Over a 5.5 ± 4.0 year mean follow-up duration, 14 patients (33%) developed MAEs. Patients with MAEs had a higher mutation load than others in urine (60.1% ± 13.8% vs. 40.6% ± 26.2%, P = 0.01) and in blood (26.9% ± 18.4% vs. 16.0% ± 12.1%, P = 0.03). Optimal cutoff values for the prediction of MAEs were 45% for urine and 35% for blood. In multivariate analysis, mutation load in urine ≥45% [odds ratio 25.3; 95% confidence interval (CI) 1.1-567.8; P = 0.04], left ventricular hypertrophy (odds ratio 16.7; 95% CI 1.3- 222.5; P = 0.03) and seizures (odds ratio 48.3; 95% CI 2.5-933; P = 0.01) were associated with MAEs. CONCLUSIONS: Patients with the m.3243A>G mutation are at high risk of MAEs, which can be independently predicted by mutation load in urine ≥45%, a personal history of seizures, and left ventricular hypertrophy.

A statistical model of the penetrating arterioles and venules in the human cerebral cortex.

OBJECTIVE: Models of the cerebral microvasculature are required at many different scales in order to understand the effects of microvascular topology on CBF. There are, however, no data-driven models at the arteriolar/venular scale. In this paper, we develop a data-driven algorithm based on available data to generate statistically accurate penetrating arterioles and venules. METHODS: A novel order-based density-filling algorithm is developed based on the statistical data including bifurcating angles, LDRs, and area ratios. Three thousand simulations are presented, and the results validated against morphological data. These are combined with a previous capillary network in order to calculate full vascular network parameters. RESULTS: Statistically accurate penetrating trees were successfully generated. All properties provided a good fit to experimental data. The k exponent had a median of 2.5 and an interquartile range of 1.75-3.7. CBF showed a standard deviation ranging from ±18% to ±34% of the mean, depending on the penetrating vessel diameter. CONCLUSIONS: Small CBF variations indicate that the topology of the penetrating vessels plays only a small part in the large regional variations of CBF seen in the brain. These results open up the possibility of efficient oxygen and blood flow simulations at MRI voxel scales which can be directly validated against MRI data.

Cardiac arrhythmia and late-onset muscle weakness caused by a myofibrillar myopathy with unusual histopathological features due to a novel missense mutation in FLNC.

Myofibrillar myopathies (MFM) are mostly adult-onset diseases characterized by progressive morphological alterations of the muscle fibers beginning in the Z-disk and the presence of protein aggregates in the sarcoplasm. They are mostly caused by mutations in different genes that encode Z-disk proteins, including DES, CRYAB, LDB3, MYOT, FLNC and BAG3. A large family of French origin, presenting an autosomal dominant pattern, characterized by cardiac arrhythmia associated to late-onset muscle weakness, was evaluated to clarify clinical, morphological and genetic diagnosis. Muscle weakness began during adult life (over 30 years of age), and had a proximal distribution. Histology showed clear signs of a myofibrillar myopathy, but with unusual, large inclusions. Subsequently, genetic testing was performed in MFM genes available for screening at the time of clinical/histological diagnosis, and desmin (DES), αB-crystallin (CRYAB), myotilin (MYOT) and ZASP (LDB3), were excluded. LMNA gene screening found the p.R296C variant which did not co-segregate with the disease. Genome wide scan revealed linkage to 7q.32, containing the FLNC gene. FLNC direct sequencing revealed a heterozygous c.3646T>A p.Tyr1216Asn change, co-segregating with the disease, in a highly conserved amino acid of the protein. Normal filamin C levels were detected by Western-blot analysis in patient muscle biopsies and expression of the mutant protein in NIH3T3 showed filamin C aggregates. This is an original FLNC mutation in a MFM family with an atypical clinical and histopathological presentation, given the presence of significantly focal lesions and prominent sarcoplasmic masses in muscle biopsies and the constant heart involvement preceding significantly the onset of the myopathy. Though a rare etiology, FLNC gene should not be excluded in early-onset arrhythmia, even in the absence of myopathy, which occurs later in the disease course.

Bethlem myopathy: long-term follow-up identifies COL6 mutations predicting severe clinical evolution.

OBJECTIVE: Mutations in one of the 3 genes encoding collagen VI (COLVI) are responsible for a group of heterogeneous phenotypes of which Bethlem myopathy (BM) represents the milder end of the spectrum. Genotype-phenotype correlations and long-term follow-up description in BM remain scarce. METHODS: We retrospectively evaluated the long-term clinical evolution, and genotype-phenotype correlations in 35 genetically identified BM patients (23 index cases). RESULTS: Nineteen patients showed a typical clinical picture with contractures, proximal weakness and slow disease progression while 11 presented a more severe evolution. Five patients showed an atypical presentation, namely a limb girdle muscle weakness in 2 and a congenital myopathy pattern with either no contractures, or only limited to ankles, in 3 of them. Pathogenic COL6A1-3 mutations were mostly missense or in frame exon-skipping resulting in substitutions or deletions. Twenty one different mutations were identified including 12 novel ones. The mode of inheritance was, autosomal dominant in 83% of the index patients (including 17% (N=4) with a de novo mutation), recessive in 13%, and undetermined in one patient. Skipping of exon 14 of COL6A1 was found in 35% of index cases and was mostly associated with a severe clinical evolution. Missense mutations were detected in 39% of index cases and associated with milder forms of the disease. CONCLUSIONS: Long-term follow-up identified important phenotypic variability in this cohort of 35 BM patients. However, worsening of the functional disability appeared typically after the age of 40 in 47% of our patients, and was frequently associated with COL6A1 exon 14 skipping.

Multi-scale homogenization of blood flow in 3-dimensional human cerebral microvascular networks.

The microvasculature plays a crucial role in the perfusion of blood through cerebral tissue. Current models of the cerebral microvasculature are discrete, and hence only able to model the perfusion over small voxel sizes before becoming computationally prohibitive. Larger models are required to provide comparisons and validation against imaging data. In this work, multi-scale homogenization methods were employed to develop continuum models of blood flow in a capillary network model of the human cortex. Homogenization of the local scale blood flow equations produced an averaged form of Darcy׳s law, with the permeability tensor encapsulating the capillary bed topology. A statistically accurate network model of the human cortex microvasculature was adapted to impose periodicity, and the elements of the permeability tensor calculated over a range of voxel sizes. The permeability tensor was found to converge to an effective permeability as voxel size increased. This converged permeability tensor was isotropic, reflecting the mesh-like structure of the cerebral microvasculature, with off-diagonal terms normally distributed about zero. A representative elementary volume of 375µm, with a standard deviation of 4.5% from the effective permeability, was determined. Using the converged permeability values, the cerebral blood flow was calculated to be around 55mLmin(-1)100g(-1), which is in very close agreement with experimental values. These results open up the possibility of future multi-scale modeling of the cerebral vascular network.

Myofibrillar myopathies: State of the art, present and future challenges.

Myofibrillar myopathies (MFM) have been described in the mid-1990s as a group of diseases sharing common histological features, including an abnormal accumulation of intrasarcoplasmic proteins, the presence of vacuoles and a disorganization of the intermyofibrillar network beginning at the Z-disk. The boundaries of this concept are still uncertain, and whereas six genes (DES, CRYAB, LDB3/ZASP, MYOT, FLNC and BAG3) are now classically considered as responsible for MFM, other entities such as FHL1 myopathy or Hereditary Myopathy with Early Respiratory Failure linked to mutations of titin can now as well be included in this group. The diagnosis of MFM is not always easy; as histological lesions can be focal, and muscle biopsy may be disappointing; this has led to a growing importance of muscle imaging, and the selectivity of muscle involvement has now been described in several disorders. Due to the rarity of these myopathies, if some clinical patterns (such as distal myopathy associated with cardiomyopathy due to desmin mutations) are now well known, surprises remain possible and should lead to systematic testing of the known genes in case of a typical histological presentation. In this paper, we aim at reviewing the data acquired on the six main genes listed above as well as presenting the experience from two French reference centres, Paris and Marseilles.

Linking Vascular Structure and Function: Image-Based Virtual Populations of the Retina.

Purpose: This study explored the relationship among microvascular parameters as delineated by optical coherence tomography angiography (OCTA) and retinal perfusion. Here, we introduce a versatile framework to examine the interplay between the retinal vascular structure and function by generating virtual vasculatures from central retinal vessels to macular capillaries. Also, we have developed a hemodynamics model that evaluates the associations between vascular morphology and retinal perfusion. Methods: The generation of the vasculature is based on the distribution of four clinical parameters pertaining to the dimension and blood pressure of the central retinal vessels, constructive constrained optimization, and Voronoi diagrams. Arterial and venous trees are generated in the temporal retina and connected through three layers of capillaries at different depths in the macula. The correlations between total retinal blood flow and macular flow fraction and vascular morphology are derived as Spearman rank coefficients, and uncertainty from input parameters is quantified. Results: A virtual cohort of 200 healthy vasculatures was generated. Means and standard deviations for retinal blood flow and macular flow fraction were 20.80 ± 7.86 µL/min and 15.04% ± 5.42%, respectively. Retinal blood flow was correlated with vessel area density, vessel diameter index, fractal dimension, and vessel caliber index. The macular flow fraction was not correlated with any morphological metrics. Conclusions: The proposed framework is able to reproduce vascular networks in the macula that are morphologically and functionally similar to real vasculature. The framework provides quantitative insights into how macular perfusion can be affected by changes in vascular morphology delineated on OCTA.

Systematic Review and Meta-Analysis of Prehospital Machine Learning Scores as Screening Tools for Early Detection of Large Vessel Occlusion in Patients With Suspected Stroke.

BACKGROUND: Enhanced detection of large vessel occlusion (LVO) through machine learning (ML) for acute ischemic stroke appears promising. This systematic review explored the capabilities of ML models compared with prehospital stroke scales for LVO prediction. METHODS AND RESULTS: Six bibliographic databases were searched from inception until October 10, 2023. Meta-analyses pooled the model performance using area under the curve (AUC), sensitivity, specificity, and summary receiver operating characteristic curve. Of 1544 studies screened, 8 retrospective studies were eligible, including 32 prehospital stroke scales and 21 ML models. Of the 9 prehospital scales meta-analyzed, the Rapid Arterial Occlusion Evaluation had the highest pooled AUC (0.82 [95% CI, 0.79-0.84]). Support Vector Machine achieved the highest AUC of 9 ML models included (pooled AUC, 0.89 [95% CI, 0.88-0.89]). Six prehospital stroke scales and 10 ML models were eligible for summary receiver operating characteristic analysis. Pooled sensitivity and specificity for any prehospital stroke scale were 0.72 (95% CI, 0.68-0.75) and 0.77 (95% CI, 0.72-0.81), respectively; summary receiver operating characteristic curve AUC was 0.80 (95% CI, 0.76-0.83). Pooled sensitivity for any ML model for LVO was 0.73 (95% CI, 0.64-0.79), specificity was 0.85 (95% CI, 0.80-0.89), and summary receiver operating characteristic curve AUC was 0.87 (95% CI, 0.83-0.89). CONCLUSIONS: Both prehospital stroke scales and ML models demonstrated varying accuracies in predicting LVO. Despite ML potential for improved LVO detection in the prehospital setting, application remains limited by the absence of prospective external validation, limited sample sizes, and lack of real-world performance data in a prehospital setting.

Predicting acute and long-term mortality in a cohort of pulmonary embolism patients using machine learning.

BACKGROUND: Pulmonary embolism (PE) is a severe condition that causes significant mortality and morbidity. Due to its acute nature, scores have been developed to stratify patients at high risk of 30-day mortality. Here we develop a machine-learning based score to predict 30-day, 90-day, and 365-day mortality in PE patients. METHODS: The Birmingham and Black Country Venous Thromboembolism registry (BBC-VTE) of 2183 venous thromboembolism patients is used. Random forests were trained on a 70% training cohort and tested against 30% held-out set. The outcomes of interest were 30-day, 90-day, and 365-day mortality. These were compared to the pulmonary embolism severity index (PESI) and simplified pulmonary embolism severity index (sPESI). Shapley values were used to determine important predictors. Oral anticoagulation at discharge was also investigated as a predictor of mortality. RESULTS: The machine learning risk score predicted 30-day mortality with AUC 0.71 [95% CI: 0.63 - 0.78] compared to the sPESI AUC of 0.65 [95% CI: 0.57 - 0.73] and PESI AUC of 0.64 [95% CI: 0.56 - 0.72]. 90-day mortality and 365-day mortality were predicted with an AUC of 0.74 and 0.73 respectively. High counts of neutrophils, white blood cell counts, and c-reactive protein and low counts of haemoglobin were important for 30-day mortality prediction but progressively lost importance with time. Older age was an important predictor of high risk throughout. CONCLUSION: Machine learning algorithms have improved on standard clinical risk stratification for PE patients. External cohort validation is required before incorporation into clinical workflows.

The Birmingham and Black Country cohort of Venous Thromboembolism (BBC-VTE) registry: Rationale, design and preliminary results.

The Birmingham Black Country Venous Thromboembolism registry (BBC-VTE) is a multi-ethnic cohort of patients who suffered a first episode of venous thromboembolism (VTE) and were admitted to various hospital sites across the West Midlands and Black Country regions in the United Kingdom. The BBC-VTE registry is a retrospective, observational cohort study which aims to collect data on outcomes including mortality, bleeding and VTE recurrence in this patient cohort. In addition, the comprehensive, structured data collected will allow us to conduct machine learning analyses for risk prediction in such patients and also to compare to previously derived mortality scores such as the PESI and the simplified PESI (sPESI). Our registry included 2183 patients admitted to hospital between the years 2012-14 and 2016-18 with a first episode of VTE and the mean follow up was 36 months. The cohort was ethnically diverse with 72.5% white Caucasian, 8.2% Asian (including South Asian), 6.7% black, and 11.7% of unknown/other ethnicity. Of those admitted during the collection period 56% had PE, 40% had DVT, with the rest presenting with both PE and DVT. Around 7% of patients went on to develop a bleeding episode and 36% died (all-cause mortality). Of the deaths, 10% of patients died within 30-days of admission (30-day mortality), with 16% dying within 90 days. In summary, this study investigates real-world outcomes of patients after the first index VTE event and attempts to bridge the gap in evidence for contemporary data in this population which will allow to construct more accurate risk prediction tools and management decisions.

Mathematical modelling of haemorrhagic transformation within a multiscale microvasculature network.

Objective.Haemorrhagic transformation (HT) is one of the most common complications after ischaemic stroke, caused by damage to the blood-brain barrier (BBB) that could be the result of stroke progression or a complication of stroke treatment with reperfusion therapy. The aim of this study is to develop further a previous simple HT mathematical model into an enlarged multiscale microvasculature model in order to investigate the effects of HT on the surrounding tissue and vasculature. In addition, this study investigates the relationship between tissue displacement and vascular geometry.Approach.By modelling tissue displacement, capillary compression, hydraulic conductivity in tissue and vascular permeability, we establish a mathematical model to describe the change of intracranial pressure (ICP) surrounding the damaged vascular bed after HT onset, applied to a 3D multiscale microvasculature. The use of a voxel-scale model then enables us to compare our HT simulation with available clinical imaging data for perfusion and cerebral blood volume (CBV) in the multiscale microvasculature network.Main results. We showed that the haematoma diameter and the maximum tissue displacement are approximately proportional to the diameter of the breakdown vessel. Based on the voxel-scale model, we found that perfusion reduces by approximately13-17%andCBVreduces by around20-25%after HT onset due to the effect of capillary compression caused by increased interstitial pressure. The results are in good agreement with the limited experimental data.Significance. This model, by enabling us to bridge the gap between the microvascular scale and clinically measurable parameters, providing a foundation for more detailed validation and understanding of HT in patients.

Pulsatile tympanic membrane displacement is associated with cognitive score in healthy subjects.

To test the hypothesis that pulsing of intracranial pressure has an association with cognition, we measured cognitive score and pulsing of the tympanic membrane in 290 healthy subjects. This hypothesis was formed on the assumptions that large intracranial pressure pulses impair cognitive performance and tympanic membrane pulses reflect intracranial pressure pulses. 290 healthy subjects, aged 20-80 years, completed the Montreal Cognitive Assessment Test. Spontaneous tympanic membrane displacement during a heart cycle was measured from both ears in the sitting and supine position. We applied multiple linear regression, correcting for age, heart rate, and height, to test for an association between cognitive score and spontaneous tympanic membrane displacement. Significance was set at P < 0.0125 (Bonferroni correction.) A significant association was seen in the left supine position (p = 0.0076.) The association was not significant in the right ear supine (p = 0.28) or in either ear while sitting. Sub-domains of the cognitive assessment revealed that executive function, language and memory have been primarily responsible for this association. In conclusion, we have found that spontaneous pulses of the tympanic membrane are associated with cognitive performance and believe this reflects an association between cognitive performance and intracranial pressure pulses.

Dunnigan lipodystrophy syndrome: French National Diagnosis and Care Protocol (PNDS; Protocole National de Diagnostic et de Soins).

Dunnigan syndrome, or Familial Partial Lipodystrophy type 2 (FPLD2; ORPHA 2348), is a rare autosomal dominant disorder due to pathogenic variants of the LMNA gene. The objective of the French National Diagnosis and Care Protocol (PNDS; Protocole National de Diagnostic et de Soins), is to provide health professionals with a guide to optimal management and care of patients with FPLD2, based on a critical literature review and multidisciplinary expert consensus. The PNDS, written by members of the French National Reference Center for Rare Diseases of Insulin Secretion and Insulin Sensitivity (PRISIS), is available on the French Health Authority website (in French). Dunnigan syndrome is characterized by a partial atrophy of the subcutaneous adipose tissue and by an insulin resistance syndrome, associated with a risk of metabolic, cardiovascular and muscular complications. Its prevalence, assessed at 1/100.000 in Europe, is probably considerably underestimated. Thorough clinical examination is key to diagnosis. Biochemical testing frequently shows hyperinsulinemia, abnormal glucose tolerance and hypertriglyceridemia. Elevated hepatic transaminases (hepatic steatosis) and creatine phosphokinase, and hyperandrogenism in women, are common. Molecular analysis of the LMNA gene confirms diagnosis and allows for family investigations. Regular screening and multidisciplinary monitoring of the associated complications are necessary. Diabetes frequently develops from puberty onwards. Hypertriglyceridemia may lead to acute pancreatitis. Early atherosclerosis and cardiomyopathy should be monitored. In women, polycystic ovary syndrome is common. Overall, the management of patients with Dunnigan syndrome requires the collaboration of several health care providers. The attending physician, in conjunction with the national care network, will ensure that the patient receives optimal care through regular follow-up and screening. The various elements of this PNDS are described to provide such a support.

The Ageing Brain: Investigating the Role of Age in Changes to the Human Cerebral Microvasculature With an in silico Model.

Ageing causes extensive structural changes to the human cerebral microvasculature, which have a significant effect on capillary bed perfusion and oxygen transport. Current models of brain capillary networks in the literature focus on healthy adult brains and do not capture the effects of ageing, which is critical when studying neurodegenerative diseases. This study builds upon a statistically accurate model of the human cerebral microvasculature based on ex-vivo morphological data. This model is adapted for "healthy" ageing using in-vivo measurements from mice at three distinct age groups-young, middle-aged, and old. From this new model, blood and molecular exchange parameters are calculated such as permeability and surface-area-to-volume ratio, and compared across the three age groups. The ability to alter the model vessel-by-vessel is used to create a continuous gradient of ageing. It was found that surface-area-to-volume ratio reduced in old age by 6% and permeability by 24% from middle-age to old age, and variability within the networks also increased with age. The ageing gradient indicated a threshold in the ageing process around 75 years old, after which small changes have an amplified effect on blood flow properties. This gradient enables comparison of studies measuring cerebral properties at discrete points in time. The response of middle aged and old aged capillary beds to micro-emboli showed a lower robustness of the old age capillary bed to vessel occlusion. As the brain ages, there is thus increased vulnerability of the microvasculature-with a "tipping point" beyond which further remodeling of the microvasculature has exaggerated effects on the brain. When developing in-silico models of the brain, age is a very important consideration to accurately assess risk factors for cognitive decline and isolate early biomarkers of microvascular health.